karnapke-routingSensornetMANET

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A Combined Routing Layer for Wireless Sensor Networks and Mobile Ad-Hoc

Networks

Tobias Senner, Reinhardt Karnapke, Andreas Lagemann, Jorg Nolte

Distributed Systems/Operating Systems Group

Brandenburg University of Technology

Cottbus, Germany

{tsenner, karnapke, ae, jon}@informatik.tu-cottbus.de

Abstract

In the near future, first responders such as firefighters

might be supported by sensor nodes, both installed beforethe incident and placed by the responders themselves. To

communicate with these sensor nodes, the first responders

could be equipped with hand held devices, e.g. PDAs with

wireless LAN, additionally equipped with a radio module of

the same type as used by the sensor nodes. This scenario

enables the usage of the PDAs as mobile communication

backbone by the sensor nodes, as well as allowing the first

responders to access nodes in the sensor network in an effi-

cient way, both near and far. This paper presents a weighted

routing protocol for heterogeneous networks, which could

be used in such a scenario.

1 Introduction

In emergency scenarios such as fires or earthquakes,

quickly deployed sensor networks can lend vital support to

first responders like firefighters and rescue teams. When

first responders arrive at the scene, they should be able

to communicate with all sensor nodes in their immediate

vicinity, or even nodes farther away, depending on the in-

tended use. An application for the former would be fire-

fighters, who measure the heat levels in the immediate area

they are moving to, using sensors that have been installed in

the building previously. An application for the latter wouldbe finding the way out of the burning building for the same

firefighters. If they dropped a few sensors on the way in,

they could determine a safe route back. When they reach

the trapped people, they would request the heat levels mea-

sured by the nodes at the entrances/exits of the building. If

the values returned from some sensors are too high, or there

is no answer at all, they would know that this route was

not safe anymore and choose a different way out. Figure 1

shows an example of such a communication. The firefight-

ers have entered the building from 3 different entrances and

planted sensor nodes on the way. Now they meet in the

center, and try do determine a safe route back out. Three ofthem request temperature values from the nodes they placed

at the entrances. For simplicity the following communica-

tion back to the firefighters is not shown here.

Another application would be the communication among

the firefighters. Currently this communication and the com-

munication between a firefighter and the operation con-

trollers is very lossy. If things go bad, and a house is about

to collapse, the controllers send an evacuation signal. But

sometimes, this signal is not received by all of the firefight-

ers, leading to danger of injuries and sometimes even death.

In our approach the evacuation order would be sent over

multiple networks - the currently used one, the wirelessLAN of the PDAs and the sensor network. The specialty

is, that the communication can switch between networks at

any time. If specified, a message of high priority like an

evacuation order received by a PDA will be flooded into the

sensor network as well as the wireless LAN. This way, even

firefighters who are not in direct communication range with

any other can be reached through multiple sensor network

hops. As this of course drains energy from the sensor nodes,

a multiple network flooding should only be used in extreme

cases, when it is absolutely vital to reach all firefighters. But

the situation mentioned before is of course such one, as the

life of the firefighters might be at stake. Figure 2 shows an

example for such a communication. The PDA in the leftupper corner just received an abort mission signal, which is

then flooded through both networks. All PDAs within range

receive it, and the corresponding firefighters evacuate. The

firefighters carrying the PDAs in the right corner would nor-

mally not have received the signal, but are now evacuating,

too, as the signal was relayed by the sensor nodes.

This paper is structured as follows: The weighted routing

protocol is described in section 2, while section 3 shows the


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Figure 1. Communication from PDAs to designated WSN nodes

Figure 2. Emergency flooding through multi-ple networks

results of the simulations and experiments we made. Re-

lated work can be found in section 4. We finish with con-

clusion and future work in section 5.

2 A Routing Protocol for Mobile Heteroge-

neous Networks

2.1 Requirements

Our scenario produces a number of requirements for the

routing protocol:

ID-based Addressing To communicate with nodes in the

immediate vicinity a local broadcast is enough. To commu-

nicate with distant nodes, a geographic approach might be

considered good. But GPS does not work inside buildings,

and GPS receivers are still too expensive, if nodes should

be used in large quantities. Other localization algorithms

are not accurate enough or take too much time. A data cen-

tered approach is not useful either. A firefighter that looks

for the way out of a burning building will not be interested

in the heat levels from all nodes in the building. Rather, only

the nodes that are near a certain exit or on the way there are

of interest. Therefore, we choose to use ID-based address-

ing. When the firefighters drop nodes, their ID is recorded

automatically, or even preprogrammed before entering.

Support for Heterogeneous Networks and Architectures

Due to the scenario, communication must be possible be-tween hand held devices and sensor nodes. We assume that

the sensor nodes are equipped with a cheap communication

module which supplies only basic functionality with little

bandwidth and low data rate. The PDAs on the other hand

use wireless LAN to communicate among each other and a

zigbee radio module to communicate with the sensor nodes.

This leads to a number of problems that have to be solved,

e.g. the different size of basic data types (8 or 16 bit for an

integer) or the internal representation of bytes (big or little

endian).

Ad-Hoc Topologies and Mobility While the Sensornodes are assumed to be immobile, the firefighters are mov-

ing through the burning building (that is their job after all).

This means that the logical topology, which denotes the

topology determined by radio neighborhood, is constantly

changing. While the connections between sensor nodes are

assumed to be fairly static, the connections between sen-

sor nodes and firefighters PDAs change often, as do those

between firefighters.


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Low Overhead for the Sensor nodes All sensor nodes

currently available have severe resource limitations. This is

valid for the memory (e.g. 10kB of Ram and 48 kB of Rom

on a TMote Sky) as well as for the communication band-

width and the energy reserves. All these make designing

a routing protocol for wireless sensor networks much more

challenging then designing one for traditional networks.

Limited Unicast and Broadcast To enable efficient col-

lective operations it is necessary to supply the ability to ad-

dress a single node within a certain range of hops (Unicast)

and to distribute messages to all nodes within a certain num-

ber of hops (n-hop Broadcast). For efficiency purposes it is

also useful to enable different forms of broadcast for the

PDAs. As they could distribute a broadcast over different

networks, it is possible to transmit only into one of them

(WSN/Manet) or into both.

Tolerance for Asymmetric and Unidirectional Links

Experiments with real networks e.g. [12] have shown that

asymmetric and even unidirectional links are quite common

in wireless sensor networks. Therefore, a way of dealing

with them has to be found.

2.2 Different Approaches to Connect Dif-ferent Networks

There is a number of different ways to connect heteroge-

neous networks. The most prominent method is inter net-

working as used in the internet. In this approach, there can

be any number of different networks (autonomous systems,

AS) with different routing strategies, that are connected.But this approach requires all nodes to have an IP-Address.

For wireless sensor networks, this approach has been shown

to be inefficient, because of the overhead of transmitting a

large IP-Header with every message, whereas the payload

is often only a few bytes.

Another solution would be to use IP-Addresses for the

PDAs, and simple IDs in the sensor network (WSN-ID).

This would require the usage of gateways for address trans-

lation or heterogeneous addressing, where each sensor node

needs to know the IP-Addresses of the PDAs it is communi-

cating with as well as the WSN-ID of its surrounding nodes.

This would lead to a lot of memory consumption on the

sensor nodes. Also, in the case of communication betweenWSN and PDAs, the IP-Address would have to be transmit-

ted, in the worst case through the whole sensor network.

A third possibility is to use a unified addressing scheme

for both networks, that is based on WSN-IDs. In this case,

the IP-Addresses of the PDAs would be ignored, and the

unified addressing used on top of raw WLAN broadcast.

This has the advantage of reducing the overhead in the

WSN.

2.3 The implemented Approach

To minimize the overhead in the sensor network, a flat

address space was chosen. The MANET nodes use the same

address type as the sensor nodes. Because the PDAs have

stronger batteries and a longer range, most of the communi-

cation should take place in the MANET. In our implementa-tion the connections between nodes are weighted with a cost

metric, which can be individually tuned. Figure 3 shows an

example where each connection involving a sensor node is

assigned a cost of 2, and pure MANET connections a cost

of 1. In this example, the node in the upper left of the sensor

net needs to communicate with the one in the lower right.

As there is a MANET nearby, this can be used as a commu-

nication backbone. The communication through the sensor

network would involve 6 nodes for a cost of 12, whereas

the communication through the MANET involves 2 sen-

sor nodes , 2 switches between the network and 3 MANET

hops, leading to a total cost of 4+4+3 = 11. The difference

becomes stronger when the difference of costs is higher.

Figure 3. Routing in a weighted heteroge-neous network

To further reduce the network load in the sensor network,

the addresses are divided into sensor identities and MANET

identities. This way, a node always knows in which network

the destination can be found. This is also useful to limit the

range of multi hop broadcasts inside either the MANET or

the sensor network.In some cases, like the afore mentioned emergency evac-

uation, a spreading through both networks is wanted. To

enable all these different scenarios, the addressing scheme

depicted in figure 4 is used. The most significant bit decides

if one or both interfaces should be used on a MANET node,

on the sensor nodes only one is available. The second bit

is used as identifier for the network the destination can be

found in. The address of the node takes up the rest of the


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Table 1. Single Hop Scenario resultspackets delivery ratio RTT min avg max

100 94% 103 ms 299 ms 537 ms

Table 1 shows the results of our measurements. The 6%packet loss can easily be explained by collisions between

route request- and acknowledgement packets. These exper-

iments were only meant to show that communication was

possible at all, but also already hint at a possible problem:

due to the usage of the Tmote as modem for the laptop, the

difference between minimal and maximal round-trip-time

(jitter) is very high.

3.2.2 MANET-MANET-WSN

The setup of the second row of experiments featured the

Tmotes and two laptops, one of which again used another

Tmote as modem. The layout of the experiment can be seenin figure 11. The laptop on top wanted to communicate with

the sensor nodes, using the laptop on the middle as a gate-

way.

Figure 11. Ping-Pong scenario setup

The results of these experiments are depicted in table 2.

It can be seen that he additional MANET hop increased the

round-trip-time by at least 95 ms, up to 284 ms. This seems

to imply (as will be shown later) that the transition between

networks and the communication on the laptop takes much

more time than that between Tmotes.

Table 2. Measured round trip time Ping-PongScenario

packets delivery ratio RTT min avg max

100 92% 198 ms 498 ms 821 ms

3.2.3 WSN-MANET-MANET-WSN

The third row of experiments featured communication be-

tween two Tmotes, using a MANET tunnel in between. In

figure 12 the sensor node on the left side wanted to transmit

to the senor node on the right side. As they were not within

range, communication was only possible using the WLAN

of the laptops in between.

Figure 12. Tunnelling WSN packets through aMANET

Table 3 shows the achieved packet delivery ratio and

round-trip-time. Note, that for all experiments no MAC

layer was used. While this was no problem for those de-

picted above, it was devastating for this setup. The rate of86% was only achieved by disabling the data packets, be-

cause they kept colliding with the next route request.

Table 3. Results of the tunnel scenariopackets delivery ratio RTT min avg max

100 86% 310 ms 514 ms 770 ms

3.2.4 WSN Multihop

In this last row of experiments only Tmotes were used,

which were arranged in a row of 2, 3 or 4 nodes. Table4 shows the results of these experiments. As suggested ear-

lier, the communication between Tmotes is fairly fast, and

the jitter is fairly low. Each hop seems to add about 30 ms

to the round trip time.

Table 4. Measured multihop round trip timeshops delivery ratio RTT min avg max

1 97% 20 ms 29 ms 30 ms

2 81% 50 ms 56 ms 60 ms

3 94% 70 ms 87 ms 100 ms

4 Related Work

The idea of adding firefighters with sensor networks has

been proposed in different ways. Sometimes the sensors are

used to find trapped people or to monitor the health status of

the firefighters themselves [4]. Siren [2] uses a tuple-space

like abstraction to exchange data about measured heat val-

ues between firefighters. The main difference between their


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approach and our is that we determine the heat levels from a

distance, whereas in theirs one of the firefighters must have

received the values directly, before forwarding them to his

colleagues.

The authors of [7] introduced TEEN and its successor

APTEEN [8]. Teen is a hierarchical cluster based routing

protocol for wireless sensor networks. In this protocol, sen-sors are gathered in groups (so called clusters), with one of

them as leader (cluster-head). Communication inside these

groups always takes place between one of the nodes and the

cluster-head. Communication between different clusters is

possible only from one cluster-head to another. In our ap-

proach the higher cost assigned to the hops between sensor

nodes leads to more of the communication taking place be-

tween the PDAs than between sensor nodes. If the number

of PDAs is high enough, and there is always a PDA within

reach of any sensor node that wants to transmit, the PDAs

would behave like the cluster-heads in TEEN.

The routing protocol AODV, which was modified for this

work was introduced in [11]. It was intended as a protocol

for MANETs, and is in its original form too heavy-weighted

to be used in sensor networks. However, with the modifica-

tions we made, we were able to adapt it to run on a Tmote

Sky without running into memory or energy problems.

Many other routing protocols for sensor networks use

different metrics. These include among others the hop

count, the minimal energy consumed along the way or the

remaining energy of each node [14, 10], or the load on par-

ticular nodes, to name but a few. Our approach also keeps

in mind the energy constraints on the sensor nodes, but not

focused on the single sensor nodes. Rather, our approach

tries to shift as much traffic as possible to the much stronger(larger battery, higher bandwidth, greater range) PDAs.

5 Conclusion and Future Work

In this paper we have presented a combined routing

protocol for sensor networks and WLAN based MANETs.

The proposed approach uses weighted connections between

nodes to determine which path to take. We have deliberately

chosen a simple metric that is not hard to compute and can

easily be implemented on resource constraint sensor nodes,

too. The results of our simulations show the advantages ofthis approach and the feasibility of the approach has been

demonstrated using a prototype implementation on Tmote

Sky sensor nodes and laptops. However, more research with

a larger number of nodes is clearly necessary. In the future,

we would like to combine this routing protocol with the col-

lective operations of COCOS [5], a high level middleware

layer that provides data parallel operations on entire groups

of sensor nodes.

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